Bank of England, Threadneedle Street, London, EC2R 8AH.The views expressed are those of the authors and do not necessarily reflect those of the Bank of England.Glenn Hoggarth and Victoria Saporta are in the Financial Industry and Regulation Division, Bank ofEngland. Ricardo Reis, who is currently at the Economics Department of Harvard University, contributedto this paper whilst working at the Bank of England. We would like to thank Stelios Leonidou and MilanKutmutia, in particular, for valuable research assistance and Patricia Jackson, Paul Tucker, Geoffrey Woodand our discussant, Patrick Honohan, for helpful suggestions. The paper has also benefited fromcomments by seminar participants at the Money, Macro and Finance Conference, held at South BankUniversity, London, September 2000 and at the Banks and Systemic Risk Conference held at the Bank ofEngland, London May 2001.Issued by the Bank of England, London, EC2R 8AH, to which requests for individual copies should be

addressed; envelopes should be marked for the attention of Publications Group. (Telephone 020-76014030.) Working Papers are also available from the Bank’s Internet site atwww.bankofengland.co.uk/workingpapers/index.htmBank of England 2001ISSN 1368-5562

ContentsAbstract

3

1

Introduction

4

2

Costs of banking crises – an overview

4

3

Measuring the costs of banking crises

6

4

Fiscal costs

7

5

Output losses

11

6

Separating out the banking crisis impact onoutput losses

20

Summary and conclusion

27

7

AbstractThis paper assesses the cross country ‘stylised facts’on empirical measures of thelosses incurred during periods of banking crises. We first consider the direct resolutioncosts to the government and then the broader costs to the welfare of the economy –proxied by losses in GDP. We find that the cumulative output losses incurred duringcrisis periods are large, roughly 15-20%, on average, of annual GDP. In contrast toprevious research, we also find that output losses incurred during crises in developedcountries are as high, or higher, on average, than those in emerging-market economies.Moreover, output losses during crisis periods in developed countries also appear to besignificantly larger – 10%-15% - than in neighbouring countries that did not at the timeexperience severe banking problems. In emerging-market economies, by contrast,banking crises appear to be costly only when accompanied by a currency crisis. Theseresults seem robust to allowing for macroeconomic conditions at the outset of crisis –in particular low and declining output growth – that have also contributed to futureoutput losses during crises episodes.

3

1. IntroductionOver the past quarter of a century, unlike the preceding twenty five years, there havebeen many banking crises around the world. Caprio and Klingebiel (1996, 1999), forexample, document 69 crises in developed and emerging market countries since thelate 1970s. In a recent historical study of 21 countries, Bordo, Eichengreen, Klingebieland Martinez-Peria (2001) report only one banking crisis in the quarter of a centuryafter 1945 but 19 since then.Although there is now a substantial cross country empirical literature on the causes ofbanking crises,a there have been fewer studies measuring the potential costs of financialsystem instability. Yet it is a desire to avoid such costs that lies behind policiesdesigned to prevent, or manage, crises. This paper considers the ways in which bankingcrises can impose costs on the broader economy and presents estimates of those costs.In particular, the paper focuses on cross-country estimates of the direct fiscal costs ofcrisis resolution and the broader welfare costs, approximated by output losses,associated with banking crises.The paper is organised as follows: Section 2 considers the various potential costs ofbanking crises and provides a brief overview of the channels through which they areincurred. Section 3 discusses briefly the general issues involved in measuring the costsof crises. Section 4 assesses the existing evidence on the fiscal costs of crisisresolution, and Section 5 presents a number of estimates of output foregone duringcrisis periods. Section 6 assesses the extent to which output losses are attributable tobanking crises per se rather than due to other causes. Section 7 concludes.

2. Costs of banking crises – an overviewA crisis in all or part of the banking sector may impose costs on the economy as awhole or parts within it. First, ‘stakeholder’in the failed bank will be directly affected.These include shareholders, the value of whose equity holdings will decline ordisappear; depositors who face the risk of losing all, or part, of their savings and thecost of portfolio reallocation; other creditors of the banks who may not get repaid; andborrowers, who may be dependent on banks for funding and could face difficulties infinding alternative sources. In addition, taxpayers may incur direct costs as a result ofpublic sector crisis resolution – cross-country estimates of these are shown below.Costs falling on particular sectors of the economy may just reflect a redistribution ofwealth, but under certain conditions banking crises may also reduce income and wealthin the economy as a whole.2.1 Potential channels of banking crisesA wave of bank failures – a banking crisis – can produce (as well as be caused by) asharp and unanticipated contraction in the stock of money and result, therefore, in arecession (Friedman and Schwartz (1963)). Secondly, if some banks fail and others arecapital constrained the supply of credit may contract, forcing firms and households toadjust their balance sheets and, in particular, to reduce spending. Output could fall inthe short-run. This mechanism – working through the ‘credit channel’– washighlighted by Bernanke (1983) who attributed the severity and length of the GreatDepression in the United States to widespread bank failure. Moreover, if investment isimpaired by a reduction in access to bank finance, capital accumulation will be reduceda

For example, see the literature review on leading indicators of banking crises by Bell and Pain (2000) and the references within.

4

and thus the productive capacity, and so output, of the economy in the longer-run willbe adversely affected.A weakened banking system can lead to a reduction in bank loans either because somebanks fail or because banks under capital pressure are limited in their ability to extendnew loans. Under the Basel Accord (which is applied in over 100 countries) banks canlend only if they can meet the specified capital requirements on the new loans. Bankscan, of course, reduce other assets to make room for bank lending but their scope todo so may be limited. Pressure on one or even several banks only will lead to apersistent reduction in the overall supply of credit, however, if other banks do not stepin to fill the gaps and borrowers cannot turn to other sources of funding such as thesecurities markets.One school of thought suggests that bank credit cannot easily be replaced by otherchannels because the intermediation function of banks is necessary for some types ofborrower (see Leland and Pyle (1977) and Fama (1985)). Collecting information onborrowers over a lengthy period enables banks to distinguish between thecreditworthiness of ‘good’and ‘bad’customers. Bank failures could lead to the loss ofthis accumulated information and impose costs on the economy in so far as theinformation has to be re-acquired. In addition the specificity of this information maymake it difficult for some borrowers to engage with a substitute bank if theirs is unableto lend (Sharpe (1990) and Rajan (1992)). In practice, the special role played by bankcredit is likely to vary from country to country, and its availability or not will beaffected by the nature and extent of crisis. In most countries, too, households and smallbusinesses at least are unlikely to be able to obtain finance from the securities markets.There are other channels too through which difficulties in the banking system (ifwidespread) can affect their customers and the economy more widely. The banks’overdraft facilities and committed back-up lines for credit are one protection againstliquidity pressures for customers, but Diamond and Dybvig (1983) also stress that byproviding an instant-access investment (demand deposits) they provide anotherimportant mechanism. Most importantly, the payments system will not work ifcustomers do not have confidence to leave funds on deposit at banks or, crucially,banks lose confidence in each other. A complete breakdown in the payments systemwould bring severe costs since trade would be impaired (see Freixas et al (2000)). Inpractice, the authorities are likely to take action before a complete loss of confidenceoccurs.The overall impact of a banking crisis on the economy depends amongst other thingson the manner and speed of crisis resolution by the authorities. For example, a policyof forbearance by regulators could increase moral hazard and harm output over anextended period, whereas a rapid clear out of bad loans might be expected to improvethe performance of the economy over the longer term. That said, such longer-runbenefits need to be weighed against any potential short-run costs of strong policyaction; for example, its effect on confidence in the financial sector more broadly.2.2 Evidence of the economy wide costs of banking crisesThere are only a limited number of cross-country comparisons of output losses ofbanking crises (see for example IMF (1998), and Bordo et al (2001)). These usesimilar methodologies and sample sizes of developed and emerging-market countriesand find that output losses during crises are, on average, in the range of 6-8% ofannual GDP for single banking crises but usually well over 10%, on average, whenbanking crises are accompanied by currency crises.5

There is some individual country evidence, albeit mainly on the United States, on thecosts of crisesb. Bernanke (1983), Bernanke and James (1991) and Bernanke (1996)provide support for the credit crunch theory of the Great Depression. Kashyap, Steinand Wilcox (1993) provide time-series evidence for the United States, that shifts inloan supply affect investment. Hall (2000) also suggests that such an effect may haveoccurred in the UK in the recession of the early 1990s. Using data from a survey ofloan officers in the US, Lown, Morgan and Rohatgi (2000) find a strong correlationbetween tighter credit standards and slower loan growth and output.In practice though, because banking sector problems are most likely to occur inrecessions, it is not easy to separate out whether a reduction in bank lending reflects areduction in the supply of or demand for funds (see Hoggarth and Thomas (1999) forthe recent situation in Japan). A critical issue, covered below, is therefore whetherreductions in output are caused by banking crises or vice versa.Cross-sectional micro-data provides further support for the special role that bankcredit performs in the economy. Kashyap, Lamont and Stein (1992) provide someevidence that non-rated firms are bank-dependent. Gertler and Gilchrist (1992) havefound that, following episodes of monetary contraction, small firms experience a largedecrease in bank loans, which appears to be their only source of external finance. Indirect contrast, large firms are able to increase their external funding by issuingcommercial paper and borrowing more from banks.

3. Measuring the costs of banking crisesSince the costs of bank failure can emerge in a variety of ways, we have adopted inwhat follows broad measures of crisis costs.There are a number of difficulties in measuring the costs of banking crises. First,defining a crisis is not straightforward. Caprio and Klingebiel (1996) cover 69 criseswhich they term either ‘systemic’(defined as when much or all of bank capital in thesystem is exhausted) or ‘border line’(when there is evidence of significant bankproblems such as bank runs, forced bank closures, mergers or government takeovers).These qualitative definitions have been used in most subsequent cross-country studies,including those in this paperc.Even when defined, measuring the costs imposed by banking crises on the economy asa whole is also not straightforward. Most cross-country comparisons of costs focus onimmediate crisis resolution. Such fiscal costs are reported in the next section. But theymay simply measure a transfer of income from taxpayers to bank ‘stakeholders’ratherthan the overall impact on economic welfared. The latter is usually proxied by thedivergence of output – and in fact the focus is often output growth - from trend duringthe banking crisis period. Estimates of these costs are also reported below in Section 5.However, these calculations estimate the output loss during the banking crisis ratherthan necessarily the loss in output caused by the crisis – the costs of banking crisis.Banking crises often occur in, and indeed may be caused by, business cycle downturns(see Gorton (1988), Kaminsky and Reinhart (1999), Demirguc-Kunt and Detragiache(1998)). Some of the estimated decline in output (output growth) relative to trendduring the banking crisis period would therefore have occurred in any case and cannotb

See Kashyap and Stein (1994) for a survey.Therefore, on this definition a crisis occurs if and when banking problems are publicly revealed rather than necessarily when the underlying problemsfirst emerge.dHowever, fiscal costs may also include a deadweight economic cost especially if the marginal costs of social funds is high.c

6

legitimately be ascribed to the crisis. In the final section below we attempt, using crosssection data, to separate declines in output during periods of banking crisis attributableto the banking crisis itself from declines due to other factors.

4. Fiscal costsTable A shows recent estimates of the fiscal costs incurred in the resolution of 24major banking crises over the past two decades, reported by Caprio and Klingebiel(1999) and Barth et al (2000). In the table a distinction has been made betweenbanking crises alone and those which occurred with a currency crisis (‘twin’crises)e. Acurrency crisis is defined, as in Frankel and Rose (1996), as a nominal depreciation inthe domestic currency (against the US dollar) of 25 per cent combined with a ten percent increase in the rate of depreciation in any year of the banking crisis periodf.Fiscal costs reflect the various types of expenditure involved in rehabilitating thefinancial system, including both bank recapitalisation and payments made to depositors,either implicitly or explicitly through government-backed deposit insurance schemes.These estimates may not be strictly comparable across countries and should be treatedwith a degree of caution. Moreover, estimates for the recent crises in east Asia may berevised, as and when new losses are recorded.That said, the data do point to some interesting stylised facts. Resolution costs appearto be particularly high when banking crises are accompanied by currency crises. Theaverage resolution cost for a twin crisis in Table A is 23 per cent of annual GDPcompared with ‘only’4 ½ per cent for a banking crisis alone. Moreover, all countriesthat had fiscal costs of more than ten per cent of annual GDP had an accompanyingcurrency crisis. Similarly, Kaminsky and Reinhart (1999) find that bail-out costs incountries which experienced a twin crisis were much larger (13 per cent of GDP), onaverage, than those which had a banking crisis alone (5 per cent).Whether the association of higher banking resolution costs with currency crises reflectsa causal relationship is unclear. On the one hand, currency crises may be more likely tooccur the more widespread and deeper the weakness in the domestic banking system,as savers seek out alternative investments, including overseas. On the other hand,currency crises may cause banking crises, or make them larger. A marked depreciationin the domestic exchange rate could result in losses for banks with large net foreigncurrency liabilities, or if banks have made loans to firms with large net foreign currencyexposures, who default on their loans. Bank losses caused in this way may beparticularly likely for countries that had fixed or quasi-fixed exchange rate regimesprior to the crisis; such regimes might have encouraged banks and other firms to runlarger unhedged currency positions than would otherwise have been the case. Manybanks made losses in this way in the recent east Asian crisis (see, for example, Drage,Mann and Michael (1998)). All the 6 countries in Table A that incurred fiscal costs ofmore than 30 per cent of GDP previously, had a fixed or quasi-fixed exchange rate inplace.The cumulative resolution costs of banking crises appear to be larger in emergingmarket economies (on average 17 ½ per cent of annual GDP) than in developed ones(12 per cent). For example, since the recent east Asian crisis, Indonesia and Thailandhave already faced very large resolution costs – 50 per cent and 40 per centrespectively of annual GDP – whereas, in the Nordic countries in the early 1990s,eAlthough the term currency ‘crisis’is used here as is common in the literature, how a large exchange rate depreciation should be viewed depends on itscause.fThe latter condition is designed to exclude from currency crises high inflation countries with large trend rates of depreciation.

7

notwithstanding widespread bank failures, cumulative fiscal costs were kept down to10 per cent or less of annual GDP. The difference may be because developed countriesface smaller shocks to their banking systems. Some data suggest that non-performingloans have been much larger in emerging market crises (see Table A)g. Alternatively,both the banking system and the real economy may have been better able to withstanda given shock because of more robust banking and regulatory systems, including betterprovisioning policies and capital adequacy practices. The difference in these fiscal costsof crisis may also reflect the greater importance of state banks within emerging markets(their share of total banking sector assets is around three times as large, on average, asin the sample of developed countries in Table Ah), since they are more likely thanprivate banks to be bailed out by governments when they fail.As one might expect, everything else equal, fiscal costs of banking resolution seem tobe larger in countries where bank intermediation - proxied by bank credit/GDP - ishigher. For example, during the Savings and Loans crisis in the United States in the1980s, where intermediation by financial institutions is relatively low by the standardsof developed countries, fiscal costs were estimated at ‘only’3 per cent of annualoutput. However, the problems were largely confined to a segment of the bankingindustry. In contrast, in Japan, where bank intermediation is relatively important, theresolution costs were estimated at 8 per cent of GDP by March 2001 and with thecurrent stabilisation package might rise as high as 17 per cent of GDPi.

g

Some caution is needed in comparing non-performing loans across countries because of differences in accountancy standards and provisioning policies.Data on state ownership are for 1997 from Barth et al (2000).iResolution costs in Japan were already estimated at 3 per cent of GDP by 1996. The current financial stabilisation package introduced in 1998 allows fora further 70 trillion Yen (14 per cent of GDP) to be spent on loan losses, recapitalisation of banks and depositor protection. But by end-March 2001 onlyan estimated 27 trillion Yen (5 per cent of GDP) of this had been spent. The current 70 trillion Yen facility is scheduled to be reduced to 15 trillion Yenin April 2002.h

Estimated at peak. Comparisons should be treated with caution since measures are dependent on country specific definitionsof non-performing loans and often non-performing loans are under-recorded.Average during the crisis period. Credit to private sector from deposit money banks (IFS code, 22d) and the figures inbrackets include also credit from other banks (IFS code, 42d).Estimates of the cumulative fiscal costs during the restructuring period expressed as a percentage of GDP.In the year the banking crisis began.Exchange rate crisis is defined as a nominal depreciation of the domestic currency (against the US dollar) of 25% or moretogether with a 10% increase in the rate of depreciation from the previous year.Resolution costs in Japan were estimated at 3% of GDP by 1996. The current financial stabilisation package introduced in1998 allows for a further 70 trillion Yen (14% of GDP) to be spent on loan losses, recapitalisation of banks and depositorprotection (the figure in brackets). But by end-March 2001 only an estimated 27 trillion Yen (5% of GDP) of this had beenspent.Cost of Savings and Loans clean up.The apparent low degree of bank intermediation in Venezuela at the time reflects the impact of high inflation on thedenominator (nominal GDP).

The qualitative stylised facts on resolution costs discussed above are summarised in thesimple regression in Table B equation (1), although the estimates should be interpretedwith caution given the small sample size (24). The point estimates suggest that, onaverage, fiscal costs are 18% of annual GDP higher when associated with a currency9

crisis, 2.2% of GDP higher for every ten percentage point higher share of credit withinGDP and 6% of GDP lower for every $10,000 increase in per capita GNP.Fiscal costs incurred almost certainly depend on how crises are resolved (see Dziobekand Pazarbasioglu (1997)). Poor resolution might be expected to be reflected in criseslasting longer and/or becoming increasingly severe. In the meantime some fragile bankscould ‘gamble for resurrection’and thus eventually require more restructuring thanwould otherwise have been the case. That said, there is no clear statistical relationshipbetween fiscal costs and crisis length for the sample of crises shown in Table A. Frydl(1999) finds a similar result. Recent work by Honohan and Klingebiel (2000),however, suggests that the approach taken to restructuring is important. This analysisof a sample of 40 developed country and emerging market crises indicates that fiscalcosts increase with liquidity support, regulatory forbearance and unlimited depositguarantees. Although we also find in our sample (weak) positive correlation betweenthe provision of liquidity support and fiscal costs, the LOLR dummy variable becomesstatistically insignificant (and wrongly signed) when added to the regressors in Table B(see equation (2)).Table B: Explanation of Fiscal Costs (% of GDP)(1)

(2)

CONST

-1.38(-0.19)

-1.23(-0.16)

CURRENCY DUMMY

17.9(2.9)

19.5(2.7)

BANK CREDIT/GDP

0.22(2.0)

0.25(1.9)

GNPP

-0.61(-1.1)

-0.65(-1.1)

LOLR

-3.4(-0.4)

Adjusted R2DW StatisticNumber of Observations

0.311.924

0.281.924

Currency Dummy

=

1 if 25% per annum nominal depreciation of the domesticexchange rate (against the US dollar) and a 10% increase in therate of depreciation in any year of the banking crisis period; 0otherwise

Bank Credit/GDP

=

Credit to private sector from deposit money banks as apercentage of annual nominal GDP (average during the crisisperiod)

GNPP

=

GNP per head (PPP-measure) in the year of the outset of thecrisis (US $000s)

LOLR

=

1 if lender of last resort is provided, 0 otherwise (source:Honohan and Klingebiel (2000))

As noted earlier, resolution costs may not always be a good measure of the costs ofcrises to the economy more generally but rather a transfer cost. Also, large fiscal costsmay be incurred to forestall a banking crisis or, at least, limit its effect. In this case, theoverall costs to the economy at large may be small, and if the crisis were avoidedwould not be observed, but significant fiscal costs might have been incurred.Conversely, the government may incur only small fiscal costs, and yet the broadereconomic adverse effects of a banking crisis could be severe. For example, a banking10

crisis was an important feature of the Great Depression of 1929-33 and yet fiscal costswere negligible since there was little capital support to the failing banks and no depositinsurance.Because of these problems in measuring losses on the basis of fiscal costs, in theremainder of the paper we concentrate mainly on a broader, and at least somewhat lesscontentious, measure of the cost of crisis – lost output.

5. Output lossesCross-country comparisons of the broader welfare losses to the economy associatedwith a banking crisis are usually proxied by losses in GDP – comparing GDP duringthe crisis period with some estimate of potential outputj. Using GDP as a proxy forwelfare though has its problems. First, welfare costs should ideally reflect losses toindividuals’current and (discounted) future consumption over their lifetime. But, inpractice, this is extremely difficult to measure. Second, changes in the level (andgrowth) of income may have more impact on individuals’utility at lower income levelsthan higher ones. This also complicates cross-country comparisons of welfare losses.There are also a number of issues in the construction of measures of output losses.5.1 Measurement issuesDefining the beginning and end of the crisisEverything else being equal, the longer a crisis lasts, the larger the (cumulative) outputlosses. The size of the measured cumulative loss will therefore be sensitive to thedefinition of the crisis period. Unfortunately, it is not straightforward to define eitherthe starting or the end point of a banking crisis.Defining the beginning of crisisSince one of the features of banks, given historic cost accounting, is that their networth is often opaque, it is difficult to assess when and whether net worth has becomenegative. One possibility is to use a marked decline in bank deposits – bank ‘runs’– asa measure of the starting point of a crisis. However, most post-war crises in developedcountries have not resulted in bank runs, whilst many crises in emerging marketcountries have followed the announcement of problems on the asset side. Bank runs,when they occur, have usually been the result rather the cause of banking crises asdefined in this article. Demirguc-Kunt, Detragiache and Gupta (2000) find, for asample of 36 developed and developing countries over the 1980-95 period, thatdeposits in the banking system did not decline during banking crises. Since bankingcrises have sometimes followed reasonably transparent problems with the quality ofbanking assets, data on a marked deterioration in the quality of banking assets and/orincreases in non-performing loans could, in principle, be used to pinpoint the timing ofthe onset of a crisis. In practice, such data are usually incomplete, unreliable or evenunavailable. Another possible approach is to measure the beginning of a crisis as thepoint when bank share prices fall by a significant amount relative to the market.However, aside from the problem of deciding what is ‘significant’, bank share price

j

An exception is a study by Boyd et al (2000) which in a sample of mainly developed country crises includes a measure of losses based on the decline inreal equity prices at the time of the crisis. The cross-country comparisons described below are dominated by emerging market countries where stockmarket prices are often unavailable.

11

indices are often unavailable for emerging market economies – the countries wheremost banking crises have occurred in recent years. Instead most studies - includingours reported below – date the beginning of crisis on a softer criterion, based on theassessment of finance experts familiar with the individual episodesk. But thesecalculations too are likely to be problematic, particularly for emerging marketeconomies. Banking problems may only become known publicly after a lag once thesituation becomes too big to hide. Moreover, even if the outbreak of the crisis can bedated, welfare losses may have been incurred beforehand because of a misallocation ofresources. So output losses incurred during crises will only capture part of the welfareloss.Defining the end of crisisAs to the end of a crisis, one possibility is to define it subjectively – say, for example,based on the expert judgement or ‘consensus’view from a range of case studies. Analternative would be to define it endogenously, for example, at the point when outputgrowth returns to its pre-crisis trend (see, for example, IMF (1998) and Aziz et al(2000)). It could be argued that this would, if anything, measure the end of theconsequences of the crisis rather than the end of the crisis itself. Both approaches arenevertheless included in our estimates reported below.Both could underestimate output losses since at the point when output growthrecovers the level of output would still be lower than it would have been otherwise. Ifinstead the end of crisis is defined as the point when the level of output returns to (theprevious) trend, the length of the crisis would be longer and thus the losses duringcrisis higher. Finally, such estimates of output losses make no attempt to measure anypossible longer-run losses or gains in output after the crisis has been resolved – forexample if the trend growth rate were permanently lowered - but this would bedifficult.Estimation of output during the crisis period in the absence of crisisTo measure the output loss during a crisis it is therefore necessary to measure actualoutput compared with its trend, or potential. The most straightforward way ofestimating output potential is to assume that output would have grown at someconstant rate based on its past performance (ie to estimate the shortfall relative to pasttrend growth). This is the approach we have used below. But this approach mayoverstate losses associated with crises if output growth fell to a lower trend during thebanking crisis period. For example, estimates of losses associated with the Japanesebanking crisis may be overstated if the growth in output potential in Japan has fallensince the early 1990s for reasons, such as an ageing population, unconnected to thecrisis.In producing comparable estimates of the shortfall in growth against trend in a largesample of countries a standardised approach to calculate trend growth, based on pastinformation, is necessary. The appropriate number of years to use in estimating thepast trend is not clear cut. A number of studies have found that banking sectorproblems often follow an economic boom (see, for example, Kindleberger (1978),Borio, Kennedy and Prowse (1996), Logan (2001)). If output growth in the run up tothe crisis was unsustainable, basing the trend growth on this period would over-

k

Caprio and Klingebiel’s (1996) extensive listing of crisis episodes seems to be the source of most subsequent studies.

12

estimate output losses during the crisis periodl . On the other hand, a banking crisis maybe preceded immediately by a marked slowdown in GDP growth (see Kaminsky andReinhart (1999) for recent crises and Gorton (1998) for a more historical perspective).The data from our sample of 47 banking crises discussed below suggest that criseshave often come after a boom in developed countries but broke at the peak of one inemerging market economiesm. Average GDP growth in the three years before criseswas above its 10 year trend in two-thirds of both the emerging market and developedcountries. For most emerging market crises, output growth was higher still in the yearimmediately prior to crisis. In contrast, in most of the developed countries, outputgrowth fell in the year before crisis.We estimate the output trend, or potential, below using both a short (3 year) and long(ten-year) window.Measuring output losses: levels versus growth ratesPerhaps the most obvious way of measuring the output loss – but one that does notappear to have been used in recent research - is to sum up the differences in the levelof annual GDP from trend during the crisis period. However, the IMF (1998), Aziz etal (2000) and Bordo et al (2001) measure output loss by summing up the differences inoutput growth rates between the pre-crisis trend and the actual rates during the crisisperiod. The output loss using the latter method approximates to the percentagedeviation in the level of actual output at the point when the crisis ends from where itwould have been had output grown at its trend rate. All other factors being equal,however, this method will understate losses associated with crises lasting for more thantwo years because it does not recognise the reduction in the output level in previousyears (a more formal explanation is given in Annex 1).Thus, other things being equal, given that crises usually last for more than two years,estimates which sum up the differences in the level of actual output from its trendduring the crisis period give a higher measure of output losses.n Below we showestimates of losses based on accumulating losses in the level and growth in output.Alternative methods used in measuring output lossesWe employed three methods of estimating the output loss - the difference betweenactual output and output assuming an absence of crisis - during the crisis period:(i)

GAP1 uses the method of the IMF (1998) and Aziz et al (2000) which definethe output loss as the sum of the differences between the growth in potential(g*) and actual output (g) during the crisis period. The authors define potentialgrowth as the arithmetic average of GDP growth in the three years prior to thecrisis and the end of crisis as the point where output growth returns to trend.More formally, let N − t 0 be the number of years for which gt < g*, i.e. output

l

In addition, it would exaggerate the length of crisis and thus estimated losses on measures that define the end of crisis when output growth returned to itspast trend. For example, the rateof output growth in Mexico has yet to return to its three year average (8 ½ per cent per annum) before the 1981-82banking crisis.mBanking crises in transitional economies have been excluded from this sample because of their special problems of transforming from a governmentowned to a market-based financial system.nIt will also yield a more accurate measure of output losses so long as the trend is not overstated.

13

growth is lower than trend growth, and let0 t be the ‘consensus’ beginning ofN

the crisis year, then GAP1 = ∑ (g * − g t ).t =t 0

(ii)

GAP2 is defined as the cumulative difference between thelevel of potentialoutput and actual output over the crisis period. The definition of crisis followsCaprio and Klingebiel (1996, 1999) based on the general opinion of countryexperts. These, in turn, define the outset of crisis when it first became publiclyknown based usually on one or more significant public events such as a forcedclosure, merger or government takeover. The end point attempts to capturewhen the banking system returns to health. Output potential is based on thetrend growth over theten-year pre-crisis period using aHodrick-Prescottfilter.o Then potential output growth is given by the last period of the filteredseries (g**). If we define dt as the percentage deviation of the level of output(Yt) from its trend level (Yt0 − 1 (1 + g ** ) t − t0 + 1 ) where t0 is the ‘consensus’ beginningN*year and N* the ‘consensus’ endpoint, then GAP 2 = ∑ d t . GAP2 should bet = t0

thought of as the deviation of the level of output from trend level (thecumulative output gap) incurred during the crisis period rather than necessarilythe costs of banking crisisper se.(iii)

GAP3, like GAP2, measuresoutput losses as the cumulative differencebetween the counterfactual and the level of actual output during the(exogenously defined) crisis period. But unlike GAP2, the counterfactual isbased on the forecast of GDP growth during the crisis period made before theoutset of the crisis rather than potential, or trend, GDP. This forecast is basedon the OECD projection for output growth over the forthcoming year madeone year before the outset of crisis. Thus GAP3 estimates are made for OECDcountries only.

These three methods were applied to our sample of 47 banking crises in developed andemerging-market economies over the 1977-98 period. Our sample comprises thecrises listed earlier on fiscal costs in Table A plus those analysed in Barthet al (2000),where the latter are given precise dates and where, for the recent crises, timely outputdata are available.5.2 ResultsTable C shows the output losses incurred during 47 banking crises on the threedifferent methods where data are available. Following Barth et al (2000), the systemiccases – shown in bold in Table C – are defined as when all, or nearly all, of the capitalin the banking system is eroded.pAlthough the estimated cumulative output losses vary markedly from crisis to crisis,there are some broad messages from Table C.

o

This is a smoothing method widely used to obtain an estimate of the long-term component of a series. Technically, the filter compares the smoothedseries yt* of yt by minimising the variance of yt* around yt subject to a penalty that constrains the second difference inyt*. We set the value of the penaltyto be equal to100 which is typical for annual data (the higher this value the smoother theyt* series).pOn the basis of GAPs 1 and 2 the Savings and Loans crisis in the United States did not result in output losses since neither the growth (GAP1), or thelevel (GAP2), of GDP in the United States fell below its past trend during the crisis in the second half of the 1980s.

14

Taking our sample of 47 countries as a whole (1977-98), the average (mean) estimatesof GAP1 – 14 ½ % - are slightly higher than those from the earlier IMF study (IMF(1998)) – 11 ½ % - which uses the same methodology. q The two sample sets of criseshave a large but not perfect overlap. In other respects, and not surprisingly given themethodologies are the same, our GAP1 estimates are similar to those from the IMFstudy. The average recovery time of output from a crisis is found to be shorter,although the cumulative losses are slightly larger, in emerging-market economies thanin developed ones.As discussed above, estimates based on summing differences in output levels fromtrend (GAP2) appear to be a better measure of losses than those based on summingdifferences in the growth of actual output from its trend (GAP1). The (mean) averagelosses using GAP2 (16 ½ % of annual GDP for all crises and 19% for systemic ones)are slightly higher than on GAP1 (14 ½ % and 17% respectively) . In contrast to boththe GAP1 estimates and the commonly held view, our GAP2 estimates suggest thatoutput losses incurred during crises are significantly higher, on average, in developedcountries than in emerging-market ones. rAs for fiscal costs, output losses during crises on both measures is usually much larger– three times and five times as large for GAP1 and GAP2 respectively - in a twin crisisthan in a banking crisis alone. For emerging-market countries, in particular, outputlosses appear significant only when a banking crisis is accompanied by a currencycrisis. Again, however, the direction of causation is unclear. One interpretation is thatexchange rate crises either lead directly to higher output losses – for example throughrequiring a tightening in monetary policy – or do so indirectly through increasing lossesfor banks with foreign currency exposures or loans to sectors which themselves havelarge currency exposures s. The latter might be expected to be a problem particularly foremerging market banking systems for which external borrowing tends to bepredominantly in foreign currency because of the cost of external borrowing indomestic currency. But causation may be the other way round, with larger bankingcrises causing a general flight from domestic assets and so putting pressure on thecurrency, which would be exacerbated if capital inflows are concentrated in thebanking sector. Another possibility is that twin crises may be more likely to occur inthe face of large adverse shocks that are themselves the main cause of the reduction inoutput (relative to trend). The leading indicator literature suggests that twin crises tendto occur against a background of weak economic fundamentals, with banking crisesmore often than not preceding currency crises which, in turn, exacerbate banking crises(see Kaminsky and Reinhart (1999)).Similar to the result found by Bordo et al (2001), we find that output losses are muchlarger where LOLR was provided. Unlike for fiscal costs discussed earlier, this resultstill holds after allowing for whether or not a banking crisis is accompanied by acurrency crisis.Table C: Accumulated Output Losses Incurred During Banking CrisesHigh Income CountriesAustralia

Date of crisis a1989-90

GAP1b %

Duration a(Years)2(0)

GAP2c %

GAP3c %

-1.4

0.0

No

-10.5

0.0

No

Currency Crisis as well

0.0dCanada

1983-85

3

0.0d

(0)

q

The IMF study is from a slightly earlier period (1975-97) and bigger sample (54).Demirguc-Kunt et al (2000) have also recently found that the slowdown in per capita GDP growth during banking crises is more persistent in developedcountries than in emerging-market ones.sHowever, the cause properly defined of the output loss here is, in fact, whatever caused the exchange rate to depreciate in the first place.r

Note: Crises in bold are judged as systemic by Barth, Caprio and Levine (2000).aCaprio and Klingebiel (1999) definition of crisis . Figures in brackets assume end of crisis is when output growth returns to trend.bIMF (1998) method. The cumulative difference between trend and actual output growth during the crisis period . Trend is the average arithmeticgrowth of output in the three-year prior to the crisis. End of crisis is when output growth returns to trendcThe cumulative difference between the trend and actual levels of output during the crisis period . Beginning and end of crisis is the Caprio andKlingebiel (1999) definition . The counterfactual path for output is based on a Hodrick-Prescott filter ten years prior to the crisis (GAP2), and OECDforecasts of GDP growth listed in country reports one year prior to the start of the crisis (GAP3). In two cases, Japan and Mexico, the country reportsgive projections that covered the whole crisis period . In all other cases the reports give projections for two years ahead. In these cases we assumed thecounterfactual growth for the later years of the crisis equal to the OECD projection for the second year of the crisis.dActual growth rate returns to trend during the first year of the crisis in Australia, Canada, France, the United States, Bolivia (1994-), Brazil, India,Indonesia (1994), Madagascar, Nigeria and Thailand (1983-87).eWhere crisis has not yet ended - Korea, Indonesia and Thailand on GAP1 plus Bolivia, India and Zimbabwe on GAP2 - costs are measured up to andincluding 1998.

5.3 Sensitivity of estimated output losses to different assumptionsThe differences in estimated losses on the GAP1 and GAP2 measures could be dueeither to differences in the assumed end-of-crisis year, differences in trend growthprofiles, and/or differences in the effect of summing up gaps in output growth fromoutput levels. In practice, the length of crisis period is usually similar under theendogenously determined method used in GAP1 or that based on ‘consensus’opinionused in GAP2 (see column 2 of Table C) . Also, in two-thirds of the sample the growthrate counterfactual is higher on GAP1 than GAP2 reflecting the stylised fact that theaverage growth rate in the three years prior to a banking crisis is usually higher than itslonger-term trend . In itself this would imply that the estimated losses using the GAP1measure should be higher than GAP2 . However, this impact is more than offset by theeffect of summing lost output levels rather than growth rates (see Table D) .Everything else equal, as crises increase in length, (cumulative) output losses rise moreon the GAP2 than the GAP1 measure . Thus GAP2 tends to be higher than GAP1when crises last for a long period such as in Japan, Spain, Peru and the Philippines andmore generally in developed countries than in emerging-markets .

Note: Average of figures reported for individual countries in Table C shown in bold.

Average loss estimates on the GAP2 measure, unlike on GAP1, are much higher fordeveloped countries (21% of annual GDP) than for emerging-market economies(14%). Moreover, the output loss estimates appear to be robust to the precise datingof crisis periods. The dates used in our GAP2 estimates are based on Barth et al (2000)and Caprio and Klingebiel (1996). As mentioned earlier, the impact on the economy ofweakness in the banking sector, especially in emerging-market countries, may haveoccurred before these dates suggest. If instead we consider the longest dating of crisesperiods for our sample of crises from a range of four studies – Caprio and Klingebiel(1996), Lindgren et al (1996), IMF (1998) and Barth et al (2000) – the mean estimatesof output losses for our whole sample rise to 22% but remain much higher indeveloped countries (28%) than in emerging-market ones (18%) t. Also, if we date thet

For the minimum definition of crisis length from these studies average output losses are 15% for the sample as a whole and 20% and 12% for high andlow/medium income countries respectively.

17

outbreak of crises in emerging-market countries one and two years earlier thansuggested in Table C, output losses, in fact, fall slightly to 13.7% and 11.8%respectively. This result occurs because, as mentioned earlier, crises in our sample ofemerging-market countries are usually immediately preceded by stronger than normaleconomic growth.Table E shows output losses per year of the crisis are a little larger, on average, fordeveloped countries than emerging-markets. But more generally there is not asignificant variation in losses per year either by length of crisis or by income. The tableillustrates that the main reason why overall losses during crises are lower for emergingmarket countries in our sample is that crisis there, unlike in developed countries, tendto be short-lived. Previous studies have also found that crises last longer, on average,in developed countries than in emerging-markets.Table E: Average Estimated GAP2 Output Losses per Year of the Crisis (percent of annual GDP)Crisis length2 years or less3-5 yearsMore than 5 yearsAll crises

All

Sample Size

4.03.86.14.3

2018947

Highincome4.15.25.64.9

Sample size66517

Low-middleincome4.03.16.84.0

Samplesize1412430

Why should banking crises last longer in developed countries? In general, financialsystems in developed countries would be expected to be more robust to shocks thanthose in emerging market countries . On the one hand, this might mean that it usuallytakes a larger shock to cause a banking crisis in a developed economy, and that thecrisis is harder to control and so longer lasting. This may be particularly likely if realwages are less flexible in developed than emerging market countries. On the other,given the greater strength of the financial system and real economy in developedcountries, the effect of a banking crisis on the economy may be initially less dramatic,giving the authorities freedom to take less radical action. The share of bad loans in thebanking system of emerging market economies at the time of the crisis is usually muchlarger than it is the case in developed countries (as shown earlier in Table A), makingthe crises initially more pronounced – banks are more likely to fail. Furthermore, thebanking system is usually a much larger part of the financial system in emerging marketeconomies than it is in developed economies, exacerbating the effect on the realeconomy. However, although crises in developed economies are likely to be lesssevere, initially, delay in resolving them is likely to increase sharply the long run loss inoutput. A recent example of this may be the drawn out Japanese banking problems,which have lasted since the early 1990s. In contrast, in lower income countries,speedier resolution mitigates the effects. A simple regression of the sample of countriesin Table A shows that a higher share of bad loans within total banking system assets isassociated with crises of shorter length (with statistical significance at the 95%confidence level). Moreover, according to Caprio and Klingebiel’s (1999) qualitativeclassification, 80% of our sample of emerging-market country crises are systemiccompared with 30% of our developed country ones (the countries listed in bold inTable C).The difference between accumulating levels rather than growth rates also explains whyin the sample of OECD countries, GAP3 estimates are usually higher than those ofGAP1. In contrast, there are marked variations, in both sign and magnitude, betweenGAP3 and GAP2 estimates. GAP3 estimates were lower than GAP2 in Finland, Japan,18

and Norway – countries which had just entered recession at the onset of crisis; buthigher in the United States and Denmark – countries in booms as banking crisis began .In fact, whereas GAP2 yields a negative output loss (ie output was above trend) duringthe US Savings and Loans crisis, GAP3 - by predicting that the US economy wouldhave enjoyed continuing growth in the absence of crisis - produces large output lossesduring the crisis.5.4 The relationship between the output losses and the resolution costs of crisisAs discussed earlier, the relationship between output losses incurred during crises andthe fiscal costs of resolution is likely to be complicated . On the one hand, the largerthe banking crisis the larger would be expected to be both the output losses incurredand the fiscal costs needed to resolve the crisis . There would be a positive associationbetween fiscal costs and output losses but no implied causation . On the other hand, tothe extent that fiscal costs are a good proxy for effective crisis resolution, the morespent by the authorities in resolving a given banking crisis the lower perhaps would bethe output losses incurred during the crisis period (ie negative correlation arising fromcausation). uLooking at the simple correlation between the fiscal costs shown earlier in Table A andoutput losses shows a positive correlation (0.6) using the GAP1 output cost measurebut little association using GAP2 (0.2) - see Table F.Table F: Correlation Matrix Between Output Losses and Fiscal CostsGAP1GAP2Fiscal costs

GAP11.000.62 (0.35)0.61

GAP21.000.18

Fiscal costs

1.00

Note: Correlations between the GAP1 and GAP2 measures of output gaps over the full sample of 47 crises shown in Table C aregiven in brackets. The rest of the correlations are computed over the sample of 24 crises listed in Table A.

Another complication between the relationship is that output losses, unlike fiscal costs,rise with the length of crisis by construction . The GAP1 and GAP2 measures of lossesare accumulated for each year of the crisis period . In fact, on the GAP2 measure, solong as the growth in output during the crisis period remains below its past trend, as isusually the case, losses per year also rise with the crisis length . However, a priori,there could be economic reasons for a positive relationship also between fiscal costsand crisis length . The longer the crisis lasts the higher might be the required resolutioncosts if in the meantime fragile banks ‘gamble for resurrection’and thus require morerestructuring than would otherwise be the case . On the other hand, the more that isspent on resolution the quicker the crisis might be resolved implying also lower outputcosts of crisis.Chart One plots fiscal costs against the length of crisis for our sample . As shown bythe line of best fit there is no clear statistical relationship between fiscal costs and crisislength. This result is similar to the findings of Frydl (1999). Although output lossesincrease with the crisis length, fiscal costs appear to be independent of the crisis length .For example, in Argentina (1980-1982) and Mexico (1994–95), where crises wereshort-lived, output costs were relatively low despite being associated with high fiscal

u

Of course, crisis resolution may result in longer-run costs to the economy to the extent that official intervention increases moral hazard.

19

costs. In contrast, in Japan, where the crisis during the 1990s was prolonged, bothoutput losses and fiscal costs have been high.The precise method and speed of fiscal resolution may be more important than thecosts incurred per se in determining the length and thus the output cost of crisis (assuggested by Dziobek and Pazarbasioglu (1997)). In Sweden, for example, despiterelatively low fiscal costs, output costs were also low because the crisis was resolvedquickly.

6. Separating out the banking crisis impact on output lossesAll the estimates of output losses during crises reported above use the differencebetween the level (or growth) in output and its past trend. But to the extent thatbanking crises coincide with, or are indeed caused by, recessions these trend growthpaths may overstate what output would have been during these periods in the absenceof banking crises. For example, the relatively large estimated output losses during theSecondary Banking Crisis (1974-76) in the UK shown in Table C more likely reflectthe impact of the recession at the time causing the banking crisis rather than vice versa.In an attempt to examine this, Bordo et al (2001) compared, for their sample ofcountries, the amount of output lost during recessions that are accompanied bybanking crises with those which are not. They find that, after allowing for other factorscausing recessions, cumulative output losses during recessions accompanied by twinand single banking crises over the 1973–97 period are around 15 per cent and 5 percent of GDP respectively deeper than those without crises. There remains thepossibility, though, that these results show partly that deeper recessions cause bankingcrises rather than vice versav.An alternative method of assessing whether these losses can be attributed to bankingcrises rather than other factors is to measure the output gaps that occurred duringthese same periods for similar countries that did not experience banking crises, or atleast, endured less severe ones. To do this, benchmark countries are needed that, inprinciple at least, are similar in all respects to the crisis countries in our sample otherthan that they did not simultaneously face a banking crisis. The idea here is that themovement in output relative to trend during the crisis period would have been, in theabsence of a banking crisis, the same or similar to the movement in the pairing country.In practice, of course, it is not possible to choose a perfect pair so that anycomparisons should be treated with a large degree of caution. Since there is notalways a clear dividing line between countries that had banking problems from thosethat did not, pairs have been made only for the episodes in our sample of outrightsystemic banking crises as defined earlier. The criteria we use to define a matchingcountry were (i) close regional proximity implying, inter alia, the likelihood ofproneness to similar shocks; (ii) similar level of GNP per capita, and (iii) similarstructure of output (measured by the shares of manufacturing, primary production(‘agriculture’) and services in GDP).The cumulative output gaps (GAP2) of the pairing countries are shown in Table G.Since crises are often clustered in regions, choosing a geographical proximate paircountry that did not also face a banking crisis is not always straightforward. Forexample, banking crises in Latin America in the early 1980s, 1990 and mid-1990saffected a number of countries in the region. This was also the case for the Nordicv

Bordo et al (2001) attempt to address this problem through using a two-stage estimation procedure.

20

banking crisis in the late 1980s/early 1990s and the east Asian crisis in 1997-98. In theNordic countries, for example, the UK has been chosen as the non-crisis pair (althoughwe also show estimates of Denmark where the crisis was judged to be non-systemic).In south east Asia in 1997-98, where the crisis affected all the countries in the region,the Philippines – a crisis country – was chosen as the ‘non-crisis’pair on the groundsthat its bad loans/GDP were much lower than in either Thailand and Indonesia – thesystemic crises in our sample. Although there are marked variations by country, theseinitial estimates suggest that the output gaps (i.e. GAP2s) during the crisis periods forthe crises countries are usually much higher than for the chosen pairs, especially inhigh-income countries. For example, output gaps in the UK and Denmark in the early1990s were far smaller than in Finland and Norway, while although output felldramatically in Korea, Thailand and Indonesia in 1997-98 it remained close to trendover the period in both Taiwan and the Philippines – the non-crises pairs. On average,banking crises increase the cumulative output gaps by 13% of GDP.

Since Korea – a comparison country for Japan 1992-98 - had a crisis itself from 1997, its output loss was estimated over the 1992-96 period and then scaledup by multiplying by 7/5 .Note : Alternative pairs used in the regression sensitivity analysis are shown in brackets. The summary statistics reported in the table, however, reflectaverages across the pairs not shown in brackets.

In Table H we report results from regressions of output gaps, on various (0,1)dummies. The table summarises the information extracted from Table F. As indicatedby the difference in the coefficient estimates on the banking crisis (BC) and non22

banking crisis dummies (1-BC) in equation (1) of the table, cumulated output lossesare 13% (ie 19%-6%) of GDP higher in our sample of systemic crises than in the noncrisis pairs. However, as indicated by the results of a standard Wald test of coefficientequality (see last two rows of column 2 of Table H), this difference is not statisticallysignificant. Within the total, output losses for crises in high and low-middle incomecountries are, on average, 25% and 10% higher respectively than in the comparablenon-crisis countries (equations (2) and (3) in columns 3 and 4). But the difference isstatistically significant only for high-income countries. Within low-middle incomecountries, the average difference in output losses between episodes of twin currencyand banking crises and episodes of banking crises alone is more than 26% of GDP(equation (4)). This difference is statistically significant at the 5% level (P-value 3%),suggesting that for low-middle income countries the incidence of currency crisis is abetter explanatory variable of cross-sectional differences in output losses than theincidence of banking crisis. Equation (5) confirms this. w Equation (6) suggests thatthis is not the case for high-income countries, where the incidence of banking crises(see equation 2) and not currency crises appears to explain better cross-sectionaldifferences in output losses.At first glance, taken together, the information from Table H suggests that theincidence of currency crisis in low-middle income countries (the CCL variable) and theincidence of banking crisis in high-income countries (the BCH variable) may indeedhelp explain the differences in output losses for the whole sample of crisis and noncrisis countries. But such an interpretation may be misleading because it ignores thepotential influence on output losses of other macroeconomic conditions prevailingprior to the year in which we start measuring output gaps which cannot be expected tobe picked up by our choice of ‘paired’non-banking crisis countries. Such conditionsmay well explain differences in output losses independently of whether the countryexperienced a banking crisis (if it was high income) or a currency crisis (if it was lowincome). In the extreme, it may turn out that such conditions explain differences inoutput losses entirely.To control for this, we run regressions for GAP2 on a range of macroeconomicvariables and on the two dummy variables: BCH and CCL (as defined in Table H). Weemployed the following variables: (i) real GDP growth (measured as the first differencein log real GDP); (ii) the change in real GDP growth; (iii) consumer price inflation(measured as the first difference in log consumer prices); (iv) growth in credit relativeto GDP (measured as the first difference in log credit over GDP); (v) fiscal deficit as apercentage of Gross National Income (or GDP when data on GNI were not available).As an alternative to (iv) we also considered the growth in the ratio of M2 to M0 butthe results reported below are insensitive to which of the two variables we use. Thesevariables were chosen on the basis of two criteria: (i) in the short run, at least,abnormal values of these variables can lead to output gaps, regardless of whether abanking crisis ensues or not, and (ii) data on these variables exist for the majority ofepisodes in our sample. Given that our sample is dominated by emerging-marketeconomies, we ruled out a number of variables that met the first criterion, but not thesecond criterion, including export volumes, the level of ( ex-post) real interest rates andthe level of terms of trade x.Table H: Regressions of GAP2a on Crisis Dummies and Significance Testsw

In section 3 we discuss briefly the possibility that the effect on fiscal costs of currency crises had been larger in countries that previously had in placefixed rather than floating exchange rate regimes prior to crisis. We tested this was the case for output losses but did not find any statistical supportingevidence.xOut of our sample of 29 systemic banking crises data were missing on exports, real interest rates and terms of trade in 8, 11 and 14 cases respectively.

23

Equation

(1)

BC

0.019

1-BC

0.061

(2)

BCH

0.320

1-BCH

0.067

(3)

BCL

0.162

1-BCL

0.061

(4)

BCL*CCL

0.272

BCL*(1-CCL)

0.090

CCL

(5)

0.227

1-CCL

-0.050

CCH

0.205

1-CCHChi-squareP-value

(6)

0.185b

1.45

5.11**

0.64

4.58**

5.33**

0.02

0.23

0.02

0.42

0.03

0.02

0.88

a

For the purposes of this regression GAP2 is in decimals rather than percentage points.This is the Chi-square statistic of a Wald test of equality between the two coefficients reported in each equation.White heteroskedasticity consistent estimators were used for all Wald tests.** Indicates rejection of the null hypothesis at the 5% level.BC= 1 if the country experienced a banking crisis and zero otherwise.BCH= 1 if a high income country experienced a banking crisis and zero otherwise.BCL= 1 if a low income country experienced a banking crisis and zero otherwise.CC= 1 if the country experienced a currency crisis and zero otherwise.CCH= 1 if a high income country experienced a currency crisis and zero otherwise.CCL= 1 if a low income country experienced a currency crisis and zero otherwise.b

As mentioned above, we are interested in a measure of how different these variablesare prior to the banking crisis compared to some measure of their normal value. Wemeasured, therefore, each variable as the difference between the average value twoyears before the banking crisis starts in a country (or in its pair for non-banking crisiscountries) and the average historical values prior to this. As an alternative, we alsomeasured each variable as the difference between the value of the variable one year(rather than averaging across two years) before a banking crisis and the averagehistorical value –but the results were insensitive to which measure we used. As iscommon in cross-sectional data, conventional diagnostic techniques reveal evidence ofheteroskedasticity. To correct for this, we estimated our regressions using an ordinaryleast squares procedure with White heteroskedasticity-consistent standard errors andcovariance matrix.The results of three specifications are reported in Table I. The second column(equation (1)) shows the results of regressing output losses on BCH and CCL and onall five of our macroeconomic variables. To test whether this regression is wellspecified, we performed a likelihood ratio redundancy test on the macroeconomicvariables that are insignificant. The test fails to reject the null hypothesis ofredundancy (Chi-square = 1.83, P-value =0.23), suggesting an alternative specificationwhere these variables are excluded - equation (2). Given that the likelihood ratio testis valid only if both the restricted (equation (2)) and unrestricted (equation (1))equations have the same number of observations, the results are reported for the 46observations that are available for all variables employed in equation (1). Equation (3)reports results of estimating equation (2) using all the observations in the sample (i.e.all the 58 crises and single pair countries shown in Table G). To check whether ourresults are sensitive to the choice of ‘paired countries’we carried out the sameprocedure substituting alternative pairs for a sample of the ‘comparison countries’(the24

‘paired’countries shown in brackets in Table G). Our inferences remained unaffected,so we do not report the results here for brevity. Our results also remain unaffected bydropping outlier estimates of output losses.Overall, the results are consistent with the information extracted from Table G.Banking crises in high-income countries and currency crises in low-middle incomecountries can explain part of the difference in output losses in the sample. Moreimportantly, however, we can now separate the losses in high-income countries due tobanking crisis from those due to differences in pre-crisis macroeconomic conditions,notably differences in changes in growth rates. In particular, on the basis of equation(3), in high-income countries, banking crises contribute, on average, around 85% tothe cumulative output losses. Taking together the fact that annual output growth fell,on average, by 1.2% in the high income countries in the two years before bankingcrises with the coefficient (-5) on this term (DDYP) in equation (3) suggests that theresidual of output losses in high income countries with banking crises (around 15%)was due to a deterioration in pre-crisis macroeconomic conditions. These estimates,however, should be interpreted with caution, particularly because our sample of highincome countries is small. In low-middle income countries, currency crises appear tocontribute 20-30 percentage points – the coefficient on the CCL dummy variable inTable I - to the accumulated output losses, but these estimates are less preciselyestimated, indicating the presence of near collinearity between the currency crisisvariable and the other variables in the equations. y Standard diagnostic tests confirmthis, suggesting that deteriorating macroeconomic conditions are associated with, andmay in part cause, subsequent currency crises. Surprisingly perhaps, such collinearityeffects, even if they do exist, do not affect significantly the precision with which thebanking crisis dummy is estimated.

yInterestingly, currency crises in the sample of low-middle income countries tend to be preceded by an increase in output growth in the two years beforecrisis.